Deterministic and Stochastic Components of Cortical Down States: Dynamics and Modulation.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Slow oscillations, characterized by Up (active) and Down (silent) states, are fundamental to cerebral cortex network activity.
• Down states are linked to unconsciousness and functionally disconnect neural networks.
• Understanding the microscale mechanisms of Down states is crucial for comprehending transitions between conscious and unconscious brain states.

Purpose of the Study:

• To investigate the detailed network dynamics and underlying mechanisms of Down states in the cerebral cortex.
• To explore how factors like anesthesia, excitability, and the excitation/inhibition balance modulate Down state dynamics.
• To propose a comprehensive model of the Up and Down state cycle that bridges mesoscale cortical properties with microscale mechanisms.

Main Methods:

• In vivo electrophysiological recordings in male mice.
• In vitro electrophysiological recordings in ferrets (either sex).
• Computational modeling (in silico) to simulate network dynamics.
• Analysis of synchronization and phase relationships during Down states under various experimental conditions.

Main Results:

• Down states exhibit metastability, comprising two distinct phases: a highly synchronized "deterministic" period followed by a low-synchronization "stochastic" period.
• The relative balance between these two phases dictates the overall dynamical properties of slow oscillations.
• This balance also governs the network's responsiveness to external inputs and its refractory period.

Conclusions:

• The identified two-phase structure of Down states provides a novel framework for understanding cortical quiescence.
• This model reconciles existing theories on slow rhythm generation and Down state function.
• The findings offer critical insights into the neural basis of switching between conscious and unconscious brain states.